Mars 520-d mission simulation reveals protracted crewhypokinesis and alterations of sleep durationand timingMathias Basnera,1,2, David F. Dingesa,1,2, Daniel Molliconeb, Adrian Eckera, Christopher W. Jonesa, Eric C. Hydera,Adrian Di Antonioa, Igor Savelevc,d, Kevin Kanb, Namni Goela, Boris V. Morukove, and Jeffrey P. Suttond,f,2

aDivision of Sleep and Chronobiology, Unit for Experimental Psychiatry, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania,Philadelphia, PA 19104; bPulsar Informatics, Inc., Philadelphia, PA 19104; cHuman Performance and Engineering Division, Wyle, Houston, TX 77058; dNationalSpace Biomedical Research Institute, Houston, TX 77030; eInstitute for Bio-Medical Problems, Moscow 123007, Russia; and fCenter for Space Medicine andDepartment of Medicine, Baylor College of Medicine, Houston, TX 77030

Edited by Joseph S. Takahashi, Howard Hughes Medical Institute and University of Texas Southwestern Medical Center, Dallas, TX, and approvedNovember 27, 2012 (received for review July 31, 2012)

The success of interplanetary human spaceflight will depend onmany factors, including the behavioral activity levels, sleep, andcircadian timing of crews exposed to prolonged microgravity andconfinement. To address the effects of the latter, we used a high-fidelity ground simulation of a Mars mission to objectively tracksleep–wake dynamics in a multinational crew of six during 520 dof confined isolation. Measurements included continuous record-ings of wrist actigraphy and light exposure (4.396 million min) andweekly computer-based neurobehavioral assessments (n = 888) toidentify changes in the crew’s activity levels, sleep quantity andquality, sleep–wake periodicity, vigilance performance, and work-load throughout the record-long 17 mo of mission confinement.Actigraphy revealed that crew sedentariness increased across themission as evident in decreased waking movement (i.e., hypokine-sis) and increased sleep and rest times. Light exposure decreasedduring the mission. The majority of crewmembers also experi-enced one or more disturbances of sleep quality, vigilance deficits,or altered sleep–wake periodicity and timing, suggesting inade-quate circadian entrainment. The results point to the need to iden-tify markers of differential vulnerability to hypokinesis and sleep–wake changes during the prolonged isolation of explorationspaceflight and the need to ensure maintenance of circadian en-trainment, sleep quantity and quality, and optimal activity levelsduring exploration missions. Therefore, successful adaptation tosuch missions will require crew to transit in spacecraft and livein surface habitats that instantiate aspects of Earth’s geophysicalsignals (appropriately timed light exposure, food intake, exercise)required for temporal organization and maintenance of humanbehavior.

sleep–wake regulation | astronaut

The success of human interplanetary spaceflight, which is an-ticipated to be in this century, will depend on the ability of

spacefarers to remain confined and isolated from Earth muchlonger than previous missions or simulations, while maintainingthe intensity and timing of behavioral activity necessary to ac-complish the mission and mitigate the effects of microgravity.A total of four people have spent >1 y in space, with the recordof 437 consecutive days on the Mir space station set by ValeryPolyakov. The longest Earth-based spaceflight simulation in-volved four Russians confined in connected hyperbaric chambersfor 240 consecutive days. Antarctic winter-over missions haveextended up to 363 d. Prediction of how prolonged confinementaffects activity levels and sleep–wake dynamics of space explor-ers is needed to inform spacecraft habitability requirements, crewselection, and behavioral countermeasures during interplanetarymissions (1–3). To address this need, we obtained objective neu-robehavioral data on the activity patterns of a multinational, cul-turally diverse crew of six males with backgrounds in engineering,

medicine, physiology, and space training, who participated ina high-fidelity ground simulation of a 520-d mission to Mars.Ecological validity of the simulation included a spaceship-likehabitat; continuous isolation from Earth’s environment; realisticmission activities; a midmission landing on a simulated Marssurface; accurate mission duration and timeline; operations be-tween crew and mission controllers; communication delays in-herent in interplanetary travel; limited consumable resources;exercise equipment for physical fitness; diurnal weekly workschedule; crew control of habitat lighting; and video monitoringof crew in habitat common areas. The simulation was developedand operated by the Institute for Bio-Medical Problems (IBMP)of the Russian Academy of Sciences. Photos of the simulationfacility and detailed descriptions of the crew, mission timeline,and work–rest schedule are provided in SI Appendix, Fig. S1 andTables S1–S3).

ResultsMovement acceleration of crewmembers was continuouslyrecorded at a 1-min resolution throughout the 520-d mission totrack the intensity and duration of active wakefulness, rest, andsleep by using validated wrist actigraphy devices that also re-corded light intensity (SI Appendix, SI Text and Fig. S2). Theresult was 4.396 × 106 min of data constituting 98.0% of timein mission. Behavioral alertness of the crew was probed twiceweekly by using psychomotor vigilance test (PVT-B) perfor-mance (4, 5) with simultaneous video of the face. Weekly crewratings were obtained for workload, tiredness, and sleep quality(SI Appendix, SI Text).

Changes in Crew Rest–Activity Dynamics During the Mission. Profilesof the crew’s time and movement intensity in discrete behavioralstates indicated increasing sedentariness across the mission.Time spent in active wakefulness per 24 h dropped sharplyduring the first 3 mo, then more gradually across the next 13 mo

Author contributions: M.B., D.F.D., D.M., A.E., C.W.J., E.C.H., A.D.A., I.S., K.K., N.G., B.V.M.,and J.P.S. designed research; M.B., D.F.D., D.M., A.E., C.W.J., E.C.H., A.D.A., I.S., K.K., N.G.,B.V.M., and J.P.S. performed research; M.B., D.F.D., D.M., C.W.J., E.C.H., A.D.A., K.K., andN.G. analyzed data; and M.B., D.F.D., C.W.J., E.C.H., A.D.A., N.G., and J.P.S. wrotethe paper.

The authors declare no conflict of interest.

This article is a PNAS Direct Submission.

Data deposition: The data reported in this paper are deposited in a Microsoft Excel file. Toaccess the data: i) Go to the www.med.upenn.edu/uep/user_documents/PNAS_Basner_et_al.xlsx. ii) When the Save File window appears, choose a destination location to save the file.1M.B. and D.F.D. contributed equally to this work.2To whom correspondence may be addressed. E-mail: dinges@mail.med.upenn.edu,basner@mail.med.upenn.edu, or jps@bcm.edu.

This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1212646110/-/DCSupplemental.

www.pnas.org/cgi/doi/10.1073/pnas.1212646110 PNAS | February 12, 2013 | vol. 110 | no. 7 | 2635–2640

NEU

ROSC

IENCE

Dow

nloa

ded

by g

uest

on

June

3, 2

020

Dow

nloa

ded

by g

uest

on

June

3, 2

020

Dow

nloa

ded

by g

uest

on

June

3, 2

020

Dow

nloa

ded

by g

uest

on

June

3, 2

020

of the mission (Fig. 1A). In the final 20 mission days, wake timeand intensity rose sharply, whereas sleep and rest times de-creased sharply relative to two preceding sequential 60-d periods(P < 0.002). Scheduled workload and crew ratings of workloaddid not increase in these final 20 d. Mission managers indicatedthat the increased activity of the crew was due to their psycho-logical anticipation of mission end.Actigraphically estimated mean sleep per 24-h day throughout

the mission was 7.39 h (SE = 0.20 h; SI Appendix, Table S5A).When corrected by −26.4 min (0.44 h) based on our validationstudy of the Actiwatch algorithm (SI Appendix, SI Text and Fig.S2), mean mission sleep duration is estimated to have been6.95 h. Because the correction estimate has a 16.8-min 95% con-fidence interval, all results reported are for uncorrected actig-raphy values. Sleep and rest times showed an inverse pattern towake time throughout the mission, increasing across the missionuntil the final 2 mo (Fig. 1A). Analyses by mission quarter (MQ;i.e., 130-d periods) revealed a 7.0% decrease in active wakefulness

across the mission, equivalent to 1.12-h less active waking perday per crewmember in the last compared with the first MQ (Fig.1B; P < 0.0001).Sleep time increased by 8.4% across the mission, equivalent to

0.59-h more sleep per day per crewmember in the last comparedwith the first MQ (Fig. 1C; P < 0.0001). Rest time increased by50.4% across the mission, equivalent to 0.54-h more rest per dayper crewmember in the last relative to the first MQ (Fig. 1D; P <0.0001). The findings were confirmed by analyses confined toonly the nocturnal (SI Appendix, Fig. S3A) or only the diurnalportion of each day (SI Appendix, Fig. S3B), which indicates thatthe time of day that active wake, rest, and sleep were obtained,did not alter the progressive sedentariness of the crew across themission. For 90% of mission time awake, crewmembers wereexposed at the wrist to light intensity of <177 lux (lx). The in-tensity of ambient light the crew was exposed to while activelyawake during the mission declined by 25.6% from a mean of104.8 lx (SE = 4.9) to a mean of 78.0 lx (SE = 8.5) across MQs

Fig. 1. Activity profiles of crewmembers measured by continuously worn wrist actigraphs throughout the 520-d simulated mission. (A) The crew’s daily mean(gray points) time (hours) spent in active wakefulness (red trend line), sleeping (blue trend line), and resting (green trend line) across the mission (for in-formation on statistical analyses, see SI Appendix, SI Text). (B–D) The crew’s mean (SE) time in each behavioral state for each consecutive 130-d MQ (red arrowshows simulated midmission landing on Mars). There was a systematic decrease across MQs in active wakefulness (B) and systematic increases in both sleeptime (C) and waking rest time (D). F test P values for these effects are shown in each graph; post hoc tests between MQs: *P < 0.05, **P < 0.01, ***P < 0.001,****P < 0.0001. (E) The crew’s daily mean (gray points) intensity of activity (counts per min) across the mission during active wakefulness (red trend line), sleep(blue trend line), and rest (green trend line). (F–H) The crew’s mean (SE) intensity of activity in each state by MQ. Activity levels declined in MQ 2 and much ofMQ 4 relative to the first MQ, but rose in the final 20 d of the last MQ (F test P values are shown in F–H). The sharp increases in active wake time (A) andintensity (E) in the final 20 mission days, and the commensurate sharp decreases in sleep and rest times (A), were significantly different from mean values forthese variables relative to two sequential 60-d periods immediately before the final 20 d of the mission (P < 0.002).

2636 | www.pnas.org/cgi/doi/10.1073/pnas.1212646110 Basner et al.

Dow

nloa

ded

by g

uest

on

June

3, 2

020

(P < 0.0001) and increased slightly during rest (SI Appendix,Fig. S3C).Integrated peak acceleration change per second was used to

evaluate movement intensity during each behavioral state. Activewaking underwent a steep decline in movement intensity duringthe first MQ, followed by a more gradual decline for 1 y and asharp rise in the final 20 mission days (Fig. 1E). Analyses of thishypokinesis by MQ confirmed reliability of the trend (Fig. 1F;P < 0.0001). The activity changes during the mission mirroredthe crew’s ratings of workload, which were highest in the firstMQ and lower in subsequent MQs (SI Appendix, Fig. S4A; F test,P < 0.0001). Crew sleep durations averaged <6.78 h (SE = 0.19 h)per day during the first 40 d of the mission, which was lower thanduring all subsequent 40-d mission periods (P < 0.05). This valueis close to actigraphically recorded sleep times of astronauts onUS Space Shuttle missions (6) and International Space Stationexpeditions, where work tempos have historically been high.Sleep durations chronically at <7 h per day result in cumula-tive neurobehavioral performance deficits across days (7, 8),making chronic partial sleep loss a risk to optimal performancein space (3).The work–rest schedule throughout the mission was 5 d on and

2 d off. The decrease in active wake and increase in sleep and resttimes as the mission progressed occurred on both work andrest days (F tests, P < 0.0001). Other than the first 40 d of themission, the only transient interruption of increasing sleep timewith mission duration involved the 80-d period before and in-cluding the midmission simulated Mars surfacing, when meansleep duration declined from 7.33 h (SE = 0.15) to 7.13 h (SE =0.22) (P = 0.0379), and crew ratings of tiredness increased(P = 0.0108).Collectively, the crew did not manifest cumulative deficits in

PVT-B vigilance performance. Crew daily sleep time increasedfrom a mean of 7.12 h in MQ 1 to 7.71 h in MQ 4 (Fig. 1C; F test,P < 0.0001), which included reliable increases in sleep durationfrom MQ 2 to 3 (post hoc test, P < 0.001) and from MQ 3 to 4(P < 0.01), when workload ratings were not changing (SI Ap-pendix, Fig. S4A). The cumulative effect of the increasing timespent asleep over the 1.42-y-long mission was substantial. In total,the crew obtained 673 h more sleep in the second half of themission relative to the first half (SI Appendix, Table S5B). Con-sistent with the increased sleep time, their average normal PVT-Bresponse speed further improved, and their already low rate ofvigilance lapses further decreased during the second half of themission (F tests, P < 0.0001; SI Appendix, Fig. S5 A and B). Thus,the added sleep in the latter half of the mission likely benefitedbehavioral alertness and psychomotor speed, and it may haveoccurred as a result of confinement, monotony, and habitatcharacteristics, which included relatively low light levels (<130 lx;SI Appendix, Fig. S3C) and privacy from monitoring camerasavailable only in areas for personal hygiene and sleeping quarters.

Variation Among Crewmembers in Sleep–Wake Activity. Cumulativefunctions were used to evaluate the degree to which changes inactivity states across the mission reflected variation in crew-member adaptation to the mission. These functions revealedsubstantial differences among crewmembers that were unrelatedto their roles, responsibilities, or workload ratings. For example,crewmember d maintained the highest wake activity level acrossthe mission (Fig. 2A) but also one of the highest sleep amounts(Fig. 2B) and the most frequent ratings of good sleep quality (SIAppendix, Table S6A). In contrast to the rest of the crew, he hada very low rest time (Fig. 2C) and a PVT-B performance errorrate that was low (Fig. 2D). His data illustrate that high wakeactivity levels and adequate sleep to maintain alertness are notincompatible in long-duration mission confinement.Crewmember f had one of the lowest wake activity levels

across the mission (Fig. 2A). He also had the lowest sleep amount

(Fig. 2B) among the crew throughout the mission (mean = 6.54 h,SE = 0.04; SI Appendix, Table S5A) and the most frequent ratingsof poor sleep quality (SI Appendix, Table S6A). He was compa-rable in rest time to most of the crew (Fig. 2C). He had a muchhigher PVT-B performance error rate than other crewmembers(Fig. 2D). He also had the majority of PVT-B facial videos dis-playing sleepiness and the most frequent ratings of difficultyperforming the PVT-B (SI Appendix, SI Text). PVT-B perfor-mance is highly sensitive to acute and chronic sleep loss and isdevoid of a learning curve (4, 9). The performance of crew-member f was consistent with his experiencing chronic partialsleep deprivation throughout the mission.There were also differences among crew in sleep–wake timing

and periodicity. Operations were organized around 24-h clocktime with a daily 8.5-h nocturnal sleep period (SI Appendix,Table S3). The crew had control over habitat lighting, food in-take, physical exercise, and other factors that can promote cir-cadian entrainment (10), but they were not exposed to Earth’sgeophysical light–dark cycle. The endogenous period of the hu-man circadian pacemaker regulating sleep–wake timing averages24.18 h (11), but it can be entrained to a 24.0-h period by certainsynchronizers, the most important being ambient light. The ap-propriate phase, intensity, duration, and spectral characteristicsof light can promote entrainment and thereby stabilize the tim-ing of behavioral states relative to environmental time, ensuringdaytime wakefulness and sleep at night (12). Measurements oflight in the crew facility revealed a spectral power distributionconsistent with fluorescent lighting (SI Appendix, Fig. S6) withlow intensity in the 446- to 477-nm wavelength region of thephoton spectrum, which is the most potent region for synchro-nizing or phase-shifting circadian rhythms of sleep and waking(13, 14) and for promoting sleep timing in polar darkness (15). Aseparate experiment sponsored by the European Space Agencyinvolved adding blue-light exposure late (days 439–499) in themission (SI Appendix, SI Text).

Fig. 2. Cumulative functions over 520 d of mission confinement for eachcrewmember’s waking activity levels (A), time spent in sleep (B) and rest (C),and PVT-B error rate (D). Examination of data from crewmembers d and fillustrate the interindividual differences among the crew in reaction to theprolonged mission confinement.

Basner et al. PNAS | February 12, 2013 | vol. 110 | no. 7 | 2637

NEU

ROSC

IENCE

Dow

nloa

ded

by g

uest

on

June

3, 2

020

Spectrographic analyses of actigraphy data across the missionwere conducted for each crewmember to evaluate the extent towhich 24-h timing of sleep–wake cycles was maintained duringthe mission (Fig. 3). Four crewmembers had a monophasic noc-turnal sleep pattern throughout the mission with a 24-h sleep–wake cycle (Fig. 3 C–F). Crewmember a manifested a split-sleeppattern (i.e., nocturnal anchor sleep plus a diurnal nap), whichbecame more pronounced in the latter half of the mission asevidenced by a 50.8% increase in diurnal sleep (Fig. 3A). Despitethis increasing displacement of sleep from the nocturnal to thediurnal portion of the day, a 24-h periodicity of sleep timing wasevident for crewmember a because a major sleep episode alwaysoccurred nocturnally.In contrast to other subjects, crewmember b had a sleep–wake

cycle with a dominant period of 24.98 h, which lengthened acrossMQs from 24.72 to 25.06 h (Fig. 3B). This prolonged sleep–wakeperiod is beyond the endogenous free-running circadian period

found in healthy adults (11), but is very similar to periods ob-served in older, shorter-duration circadian isolation protocols(17) and polar studies (18), wherein subjects had access to room-light exposure before circadian temperature minimum. A num-ber of factors may contribute to a prolonged sleep–wake cycleduring confinement and isolation, including exercise (19) andlight exposure at sensitive portions of the circadian-phase re-sponse curve for each zeitgeber (11). The circadian system issensitive to even low levels of light before body temperatureminimum (20), which can induce phase delays in molecularmechanisms of entrainment (21), suppress melatonin secretion(13), and induce longer sleep–wake periods (22). Examination oflight-exposure data revealed that crewmember b was awake laterat night and exposed to light at times that may have contributedto repeated phase delays of his sleep–wake cycle (23, 24). Thisnocturnal room-light exposure during a sensitive phase for cir-cadian delays began in the first 30 d of the mission (SI Appendix,

Fig. 3. Double raster plots of sleep (black) and wake (white) and spectral plots (blue and yellow) from actigraphically derived sleep and waking throughoutthe 520-d mission for crewmembers a, b, c, d, e, and f (A–F, respectively). Rest was classified as wake for these analyses. Spectral analyses to evaluate sleep–wake periodicity were performed on 1-min actigraphic epochs based on the power spectral density by using the periodogram method (16), multiplying thedata with a 90-d rectangular window and taking the squared magnitude of the discrete time Fourier transform. The peak frequency was estimated by a 3-point quadratic interpolation based on the log-magnitudes of the periodogram at the frequency corresponding to the maxima in the periodogram and thetwo neighboring points. Spectrogram plots were derived from the 90-d window moved in increments of 10 d across the mission (SI Appendix, SI Text). As isevident in the double-raster and spectral plots, all crewmembers except b had a predominant 24-h sleep–wake periodicity. Crewmember b had a sleep–wakeperiod that varied between 24.72 and 25.06 h across the mission, increased with time in mission, and averaged 24.98 h for the entire mission. The smaller 24-hpeak seen in the spectrogram of crewmember b was due to his daily attendance at breakfast between 08:00 and 10:00 each morning (SI Appendix, Table S3).

2638 | www.pnas.org/cgi/doi/10.1073/pnas.1212646110 Basner et al.

Dow

nloa

ded

by g

uest

on

June

3, 2

020

Fig. S7A) and occurred periodically thereafter as the sleep–wakecycle lengthened to near 25 h (SI Appendix, Fig. S7B).The near 25-h sleep–wake period of crewmember b (Fig. 3B)

and the biphasic sleep pattern of crewmember a (Fig. 3A) wereassociated with more mission days in which their total sleeptimes was >10 h (12.6% and 12.2%, respectively) relative to allother crewmembers (mean = 1.7%). They were the only twocrewmembers who showed average delayed sleep onset times of∼2 h or more during the first month of the mission relative totheir premission averages—3 h 22 min for crewmember b and 1 h59 min for crewmember a (SI Appendix, SI Text and Table S4).This result is consistent with both crewmembers experiencingdelayed sleep-phase syndrome or non-24-h sleep–wake syn-drome (25). The longer-duration sleep episodes and increasedtemporal displacement of sleep resulted in these two crew-members being asleep when other crewmembers were awake (orvice versa) a total of 2,498 h, or 20.1% of the mission (SI Ap-pendix, Fig. S7C). Such unplanned temporal desynchrony amongcrewmembers has the potential to pose a challenge for effectivecrew coordination during long-duration spaceflight.

DiscussionA majority (four of six) of the crewmembers in this record-long,high-fidelity, simulated space mission confinement experiencedone or more of the following problems: disrupted sleep–wakeperiodicity (n = 1), increased displacement of sleep into the di-urnal period (n = 2), performance deficits associated withchronic partial sleep deprivation (n = 1), and frequent reductionsin perceived sleep quality (n = 2). Spectral plots (Fig. 3) andcumulative functions (Fig. 2) indicate that these problems oc-curred early in the mission and persisted unabated. Such in-dividual differences in disturbances of sleep–wake regulation aresimilar to those identified in winter-over polar expeditions (15,26), which are often considered analogs for the study of behav-ioral reactions to the prolonged isolation of spaceflight (27–30).The fact that sleep–wake disruptions occur during confinementand isolation in some individuals more than others is consistentwith increasing evidence that there are phenotypic and genotypicdifferences in vulnerability to both alterations of sleep and theresulting neurobehavioral consequences (31–37). This differen-tial vulnerability has led to a search for predictive biomarkers ofthe effects of sleep loss (38), which would be useful for managingsleep–wake regulation during exploration spaceflight (39).The progressive sedentariness of the crew that was evident

through increased sleep and rest times and the decreased activewakefulness with time in mission support the view that ecologicalvariables can be determinants of human sleep duration (40). It issuggestive of behavioral aspects of torpor, which historicallyrefers to lethargy (41) but more recently has been used to definemetabolic or body temperature changes characteristic of heter-othermic mammals and birds (42). The concept of behavioraltorpor as sedentariness is consistent with the increases in sleepreported in some migratory birds and other animals living inconfinement or during winter photoperiods (43, 44).The hypokinesis and behavioral torpor during the 520-d sim-

ulated exploration mission, the sleep loss induced by criticalperiods of high workload early in the mission, and the commonand persistent disturbances of sleep–wake behaviors throughoutthe mission highlight the importance of preventing these con-ditions in exploration missions. There is a need for novel spaceexploration habitats and crew activity schedules that mimic thebiological potency of Earth’s geophysical cycle through bothphotic (22, 45) and nonphotic (10, 19, 46) synchronizers to pro-mote circadian entrainment and the temporal optimization ofbehavioral states during prolonged spaceflight. These needs ex-tend to circadian adjustment for work in near-circadian environ-ments, such as the Martian solar day (i.e., 24.67 h) (47). A balancemust be struck during human exploration of space between the

critical need for adequate time for sleep and rest and the needto maintain activity levels for physical and physiological fitness.This balance is especially important given the deleterious effectsof prolonged microgravity on the musculoskeletal, cardiovascular(48), and other systems (49) and the requirement to sustain fit-ness to work effectively, avoid injury, and successfully accomplishthe mission.Our findings also have implications for the increasing preva-

lence of sleep and circadian rhythm disorders among humansliving on Earth in industrialized societies, with limited exposureto natural geophysical signals, widespread sedentary activities,and primarily artificial light exposure. There is considerablepopulation evidence that work schedules (50), alarm clocks (51),television programming times (51), and cultural time shifts, suchas school start times (52) and daylight savings time (53), con-tribute to sleep restriction and a discrepancy between circadianand social clocks (i.e., social jetlag), both of which have beenlinked to obesity (54). The essential need for humans to maintainsleep–wake activity cycles synchronized to the circadian biologythat temporally coordinates human health and behavior appearsto be as important on Earth as it will be en route to Mars.

MethodsThe State Scientific Center of the Russian Federation–IBMP of the RussianAcademy of Sciences (RAS) performed the 520-d simulated mission. Crew-members signed informed consents approved by the Institutional ReviewBoard of the University of Pennsylvania.

Wrist actigraphy (Actiwatch Spectrum; Philips/Respironics) for assessingsleep–wake activity (55) was worn by crewmembers throughout the 520 d.Both average light intensity and movement-induced accelerations at thewrist were recorded in 1-min epochs. Activity data were classified intoactive wake, sleep, or waking rest using Respironics Actiware (Version5.59.0015). A separate validation study that we conducted of the Acti-watch state scoring algorithm established its detection sensitivity for sleepat 97.0%, its specificity for wakefulness at 96.2%, and overall accuracy ofthe Actiwatch algorithm at 96.4% (SI Appendix, SI Text and Fig. S2). A totalof 4,396,333 min of activity was collected in the 520-d mission, which was98.02% of the total possible. Actigraphy was also used to evaluate theintensity of activity for each 24-h period during the mission and in each ofthe three states.

Spectrographic analyses of actigraphy data were performed on 1-minepochs to determine the predominant periodicity of sleep–wake timing foreach subject. Power spectra of the sleep–wake time series were estimatedby using the periodogram method (16) of multiplying the data with a 90-drectangular window and taking the squared magnitude of the discrete timeFourier transform.

Behavioral alertness was assessed by using psychomotor vigilance per-formance (refs. 4, 9, and 56; SI Appendix, SI Text) on a 3-min test (PVT-B) thatwas obtained weekly (once in the morning, once in the evening) by com-puter (4), with 100% complete data acquisition (n = 888 tests). Facial videoswere recorded at 30 frames per second during each PVT-B and evaluated forslow eyelid closures indicative of sleepiness (57). Immediately before or aftereach PVT-B test, crewmembers completed computerized scales that included100-mm visual analog scales with the following binary anchors: good/poorsleep quality (morning only), high/low workload (evening only), and high/low tiredness (evening only). Data acquisition for these subjective ratingswas 100% (n = 444).

Mixed-model ANOVAs (Proc Mixed; Version 9.3; SAS Institute) with arandom intercept for crewmembers and unstructured covariance were per-formed with 130-d MQs as the explanatory variable. If a type 3 test indicateda significant MQ effect (P < 0.05), two-sided post hoc t tests comparing in-dividual MQs were performed. Fig. 1 and SI Appendix, Figs. S3–S5 graphicallypresent these analyses. Significant findings of post hoc tests are indicated(*P < 0.05, **P < 0.01, **P < 0.001, ****P < 0.0001). All statistical tests weretwo-tailed.

ACKNOWLEDGMENTS. The Mars 520-d simulation was developed by theInstitute for Biomedical Problems of the Russian Academy of Sciences. Wethank A. I. Grigoriev, I. B. Ushakov, E. P. Demin, and M. S. Belakovskiyfor creating the simulation; the crew for participating in the study andproviding the data; the crew of the 105-d pilot study for helping identifythe optimal data acquisition techniques; E. Carota Orne for supporting theproject; and D. Metaxas, C. Mott, R. Bartels, S. Arroyo, X. Yu, and J. Allen

Basner et al. PNAS | February 12, 2013 | vol. 110 | no. 7 | 2639

NEU

ROSC

IENCE

Dow

nloa

ded

by g

uest

on

June

3, 2

020

for aiding in data extraction. The research was supported by theNational Space Biomedical Research Institute through National Aero-nautics and Space Administration cooperative agreement NCC 9-58 and

by the Institute for Experimental Psychiatry Research Foundation. TheFriedkin Chair for Research in Sensory System Integration and SpaceMedicine (J.P.S.) is also acknowledged.

1. Ball JR, Evans CH, eds (2001) Safe Passage: Astronaut Care for Exploration Missions(National Academy Press, Washington).

2. NASA, Human Research Roadmap: A Risk Reduction Strategy for Human Space Ex-ploration. Available at http://humanresearchroadmap.nasa.gov/. Accessed July 31,2012.

3. Whitmire AM, et al. (2009) Risk of Performance Errors due to Sleep loss, CircadianDesynchronization, Fatigue and Work Overload: NASA Evidenced-Based Review(NASA, Washington), Human Research Program Requirements Document HRP-47052,Rev. C.

4. Basner M, Mollicone D, Dinges DF (2011) Validity and sensitivity of a brief psycho-motor vigilance test (PVT-B) to total and partial sleep deprivation. Acta Astronaut69(11-12):949–959.

5. Basner M, Rubinstein J (2011) Fitness for duty: A 3-minute version of the PsychomotorVigilance Test predicts fatigue-related declines in luggage-screening performance.J Occup Environ Med 53(10):1146–1154.

6. Dijk DJ, et al. (2001) Sleep, performance, circadian rhythms, and light-dark cyclesduring two space shuttle flights. Am J Physiol Regul Integr Comp Physiol 281(5):R1647–R1664.

7. Van Dongen HPA, Maislin G, Mullington JM, Dinges DF (2003) The cumulative cost ofadditional wakefulness: dose-response effects on neurobehavioral functions andsleep physiology from chronic sleep restriction and total sleep deprivation. Sleep26(2):117–126.

8. Belenky G, et al. (2003) Patterns of performance degradation and restoration duringsleep restriction and subsequent recovery: A sleep dose-response study. J Sleep Res12(1):1–12.

9. Lim J, Dinges DF (2008) Sleep deprivation and vigilant attention. Ann N Y Acad Sci1129:305–322.

10. Fuller PM, Lu J, Saper CB (2008) Differential rescue of light- and food-entrainablecircadian rhythms. Science 320(5879):1074–1077.

11. Czeisler CA, et al. (1999) Stability, precision, and near-24-hour period of the humancircadian pacemaker. Science 284(5423):2177–2181.

12. Duffy JF, Wright KP, Jr. (2005) Entrainment of the human circadian system by light.J Biol Rhythms 20(4):326–338.

13. Brainard GC, et al. (1988) Dose-response relationship between light irradiance andthe suppression of plasma melatonin in human volunteers. Brain Res 454(1-2):212–218.

14. Dijk DJ, et al. (2012) Amplitude reduction and phase shifts of melatonin, cortisol andother circadian rhythms after a gradual advance of sleep and light exposure in hu-mans. PLoS ONE 7(2):e30037.

15. Mottram V, Middleton B, Williams P, Arendt J (2011) The impact of bright artificialwhite and ‘blue-enriched’ light on sleep and circadian phase during the polar winter.J Sleep Res 20(1 Pt 2):154–161.

16. Hayes MH (1996) Statistical Digital Signal Processing and Modelling (John Wiley &Sons, New York).

17. Aschoff J, Wever R (1962) Spontanperiodik des menschen bei ausschluß aller zeit-geber [Spontaneous periodicity in humans under exclusion of all zeitgebers]. Natur-wissenschaften 49(15):337–342. German.

18. Kennaway DJ, Van Dorp CF (1991) Free-running rhythms of melatonin, cortisol,electrolytes, and sleep in humans in Antarctica. Am J Physiol 260(6 Pt 2):R1137–R1144.

19. Barger LK, Wright KP, Jr., Hughes RJ, Czeisler CA (2004) Daily exercise facilitates phasedelays of circadian melatonin rhythm in very dim light. Am J Physiol Regul IntegrComp Physiol 286(6):R1077–R1084.

20. Khalsa SB, Jewett ME, Cajochen C, Czeisler CA (2003) A phase response curve to singlebright light pulses in human subjects. J Physiol 549(Pt 3):945–952.

21. Schwartz WJ, Tavakoli-Nezhad M, Lambert CM, Weaver DR, de la Iglesia HO (2011)Distinct patterns of Period gene expression in the suprachiasmatic nucleus underliecircadian clock photoentrainment by advances or delays. Proc Natl Acad Sci USA108(41):17219–17224.

22. Lockley SW, Brainard GC, Czeisler CA (2003) High sensitivity of the human circadianmelatonin rhythm to resetting by short wavelength light. J Clin Endocrinol Metab88(9):4502–4505.

23. Gronfier C, Wright KP, Jr., Kronauer RE, Czeisler CA (2007) Entrainment of the humancircadian pacemaker to longer-than-24-h days. Proc Natl Acad Sci USA 104(21):9081–9086.

24. Zeitzer JM, Dijk DJ, Kronauer RE, Brown EN, Czeisler CA (2000) Sensitivity of thehuman circadian pacemaker to nocturnal light: Melatonin phase resetting and sup-pression. J Physiol 526(Pt 3):695–702.

25. Okawa M, Uchiyama M (2007) Circadian rhythm sleep disorders: Characteristics andentrainment pathology in delayed sleep phase and non-24-h sleep-wake syndrome.Sleep Med Rev 11(6):485–496.

26. Arendt J (2012) Biological rhythms during residence in polar regions. Chronobiol Int29(4):379–394.

27. Stuster J (2004) Lessons from previous expeditions for the human exploration of Mars.J Brit Interplanet Soc 57(3–4):126–134.

28. Kanas N, et al. (2009) Psychology and culture during long-duration space missions.Acta Astronaut 64(7–8):659–677.

29. Palinkas LA, Suedfeld P (2008) Psychological effects of polar expeditions. Lancet371(9607):153–163.

30. Leon GR, Sandal GM, Larsen E (2011) Human performance in polar environments.J Environ Psychol 31(4):353–360.

31. Franken P, Chollet D, Tafti M (2001) The homeostatic regulation of sleep need isunder genetic control. J Neurosci 21(8):2610–2621.

32. Van Dongen HPA, Baynard MD, Maislin G, Dinges DF (2004) Systematic interindividualdifferences in neurobehavioral impairment from sleep loss: Evidence of trait-likedifferential vulnerability. Sleep 27(3):423–433.

33. Viola AU, et al. (2007) PER3 polymorphism predicts sleep structure and waking per-formance. Curr Biol 17(7):613–618.

34. Landolt HP (2008) Genotype-dependent differences in sleep, vigilance, and responseto stimulants. Curr Pharm Des 14(32):3396–3407.

35. Goel N, Banks S, Mignot E, Dinges DF (2010) DQB1*0602 predicts interindividualdifferences in physiologic sleep, sleepiness, and fatigue. Neurology 75(17):1509–1519.

36. Dijk DJ, Archer SN (2010) PERIOD3, circadian phenotypes, and sleep homeostasis.Sleep Med Rev 14(3):151–160.

37. Kuna ST, et al. (2012) Heritability of performance deficit accumulation during acutesleep deprivation in twins. Sleep 35(9):1223–1233.

38. Czeisler CA (2011) Impact of sleepiness and sleep deficiency on public health—utilityof biomarkers. J Clin Sleep Med 7(5, Suppl):S6–S8.

39. Goel N, Dinges DF (2012) Predicting risk in space: Genetic markers for differentialvulnerability to sleep restriction. Acta Astronaut 77:207–213.

40. Siegel JM (2009) Sleep viewed as a state of adaptive inactivity. Nat Rev Neurosci10(10):747–753.

41. Simpson JA, Weiner ESC, eds (1989) Oxford English Dictionary (Oxford Univ Press,New York), 2nd Ed.

42. Carey HV, Andrews MT, Martin SL (2003) Mammalian hibernation: Cellular and mo-lecular responses to depressed metabolism and low temperature. Physiol Rev 83(4):1153–1181.

43. Jones SG, Paletz EM, Obermeyer WH, Hannan CT, Benca RM (2010) Seasonal influ-ences on sleep and executive function in the migratory White-crowned Sparrow(Zonotrichia leucophrys gambelii). BMC Neurosci 11:87.

44. Siegel JM (2008) Do all animals sleep? Trends Neurosci 31(4):208–213.45. Scheer FAJL, Wright KP, Jr., Kronauer RE, Czeisler CA (2007) Plasticity of the intrinsic

period of the human circadian timing system. PLoS ONE 2(8):e721.46. Buxton OM, Lee CW, L’Hermite-Baleriaux M, Turek FW, Van Cauter E (2003) Exercise

elicits phase shifts and acute alterations of melatonin that vary with circadian phase.Am J Physiol Regul Integr Comp Physiol 284(3):R714–R724.

47. Barger LK, et al. (2012) Learning to live on a Mars day: fatigue countermeasuresduring the Phoenix Mars Lander mission. Sleep 35(10):1423–1435.

48. Fu Q, et al. (2002) Cardiovascular and sympathetic neural responses to handgrip andcold pressor stimuli in humans before, during and after spaceflight. J Physiol 544(Pt2):653–664.

49. Zayzafoon M, Meyers VE, McDonald JM (2005) Microgravity: The immune responseand bone. Immunol Rev 208(1):267–280.

50. Basner M, et al. (2007) American Time Use Survey: Sleep time and its relationship towaking activities. Sleep 30(9):1085–1095.

51. Basner M, Dinges DF (2009) Dubious bargain: Trading sleep for Leno and Letterman.Sleep 32(6):747–752.

52. Wittmann M, Dinich J, MerrowM, Roenneberg T (2006) Social jetlag: Misalignment ofbiological and social time. Chronobiol Int 23(1-2):497–509.

53. Kantermann T, Juda M, Merrow M, Roenneberg T (2007) The human circadian clock’sseasonal adjustment is disrupted by daylight saving time. Curr Biol 17(22):1996–2000.

54. Roenneberg T, Allebrandt KV, Merrow M, Vetter C (2012) Social jetlag and obesity.Curr Biol 22(10):939–943.

55. Ancoli-Israel S, et al. (2003) The role of actigraphy in the study of sleep and circadianrhythms. Sleep 26(3):342–392.

56. Basner M, Dinges DF (2011) Maximizing sensitivity of the psychomotor vigilance test(PVT) to sleep loss. Sleep 34(5):581–591.

57. Abe T, et al. (2011) Detecting deteriorated vigilance using percentage of eyelid clo-sure time during behavioral maintenance of wakefulness tests. Int J Psychophysiol82(3):269–274.

2640 | www.pnas.org/cgi/doi/10.1073/pnas.1212646110 Basner et al.

Dow

nloa

ded

by g

uest

on

June

3, 2

020

Corrections

NEUROSCIENCECorrection for “Mars 520-d mission simulation reveals protractedcrew hypokinesis and alterations of sleep duration and timing,”by Mathias Basner, David F. Dinges, Daniel Mollicone, AdrianEcker, Christopher W. Jones, Eric C. Hyder, Adrian Di Antonio,Igor Savelev, Kevin Kan, Namni Goel, Boris V. Morukov, andJeffrey P. Sutton (first published January 7, 2013; 10.1073/pnas.1212646110).The authors note that Fig. 2 appeared incorrectly. The authors

unintentionally labeled the ordinate of Fig. 2A “cumulative wakeactivity (×104)” instead of “cumulative wake activity (counts/min ×107)”, and they unintentionally labeled the parenthetical metricon the ordinate of Fig. 2D as “(h × 102)” when it should havebeen “(×102)”.The corrected figure and its legend appear below. These errors

do not affect the conclusions of the article.

www.pnas.org/cgi/doi/10.1073/pnas.1301039110

PSYCHOLOGICAL AND COGNITIVE SCIENCESCorrection for “Reduced sensitivity to emotional prosody incongenital amusia rekindles the musical protolanguage hypothesis,”by William Forde Thompson, Manuela M. Marin, and LaurenStewart, which appeared in issue 46, November 13, 2012, of ProcNatl Acad Sci USA (109:19027–19032; first published October 29,2012; 10.1073/pnas.1210344109).The authors note that two column headings in Table 3 appeared

incorrectly. “F0 (Hz)” should instead appear as “Log F0 (ST)”measured as 12*log2(F0), or the number of semitones from 1 Hz,where middle C (261.626 Hz) has an approximate value of 96.“SD F0” should instead appear as “SD (ST)”. Statistical analysesof the fundamental frequency of speech stimuli were also basedon 12*log2(F0). The corrected table appears below. This errordoes not affect the conclusions of the article.

www.pnas.org/cgi/doi/10.1073/pnas.1222350110Fig. 2. Cumulative functions over 520 d of mission confinement for eachcrewmember’s waking activity levels (A), time spent in sleep (B) and rest (C),and PVT-B error rate (D). Examination of data from crewmembers d andf illustrate the interindividual differences among the crew in reaction to theprolonged mission confinement.

Table 3. Acoustical features of the Macquarie Battery ofEmotional Prosody

EmotionLog F0(ST)

SD(ST)

Contourchanges Slope

Duration(s)

Intensity(dB)

HappyM 93.44 3.92 8.13 5.00 2.85 73.99SEM 1.17 0.22 0.30 7.74 0.12 0.39

TenderM 86.99 3.34 6.50 −13.51 3.24 68.76SEM 1.94 0.33 0.27 4.45 0.15 0.39

AfraidM 93.46 1.69 7.56 −17.54 2.31 74.80SEM 1.97 0.13 0.34 3.77 0.08 0.56

IrritatedM 91.98 2.97 5.63 −30.15 2.43 73.76SEM 1.12 0.24 0.44 9.00 0.08 0.83

SadM 87.49 2.88 6.94 −11.98 3.10 68.76SEM 1.75 0.42 0.40 3.31 0.13 0.89

NoEmotionM 87.01 2.64 6.81 −15.30 2.90 71.66SEM 1.65 0.22 0.29 4.25 0.11 0.72

ST, semitones from 1 Hz, or 12*log2(F0); M, mean; SD, standard deviation;SEM, standard error of the mean.

2676–2677 | PNAS | February 12, 2013 | vol. 110 | no. 7 www.pnas.org

MICROBIOLOGYCorrection for “Evolution of the receptor binding properties ofthe influenza A(H3N2) hemagglutinin,” by Yi Pu Lin, Xiaoli Xiong,Stephen A. Wharton, Stephen R. Martin, Peter J. Coombs,Sebastien G. Vachieri, Evangelos Christodoulou, Philip A. Walker,Junfeng Liu, John J. Skehel, Steven J. Gamblin, Alan J. Hay,Rodney S. Daniels, and John W. McCauley, which appearedin issue 52, December 26, 2012, of Proc Natl Acad Sci USA(109:21474–21479; first published December 10, 2012; 10.1073/pnas.1218841110).The authors note that on page 21474, within the Data Deposition

footnote, the URL “http://platform.gisaid.org/epi3/” should insteadappear as “http://gisaid.org/”.

www.pnas.org/cgi/doi/10.1073/pnas.1222337110

IMMUNOLOGYCorrection for “Essential role of MALT1 protease activity inactivated B cell-like diffuse large B-cell lymphoma,” by StephanHailfinger, Georg Lenz, Vu Ngo, Anita Posvitz-Fejfar, FabienRebeaud, Montserrat Guzzardi, Eva-Maria Murga Penas, JudithDierlamm, Wing C. Chan, Louis M. Staudt, and Margot Thome,which appeared in issue 47, November 24, 2009, of Proc NatlAcad Sci USA (106: 19946-19951; first published November 6,2009; 10.1073/pnas.0907511106).The authors note that data reported in this article have been

deposited in the Gene Expression Omnibus (GEO) database,www.ncbi.nlm.nih.gov/geo (accession no. GSE41034).

www.pnas.org/cgi/doi/10.1073/pnas.1300336110

PNAS | February 12, 2013 | vol. 110 | no. 7 | 2677

CORR

ECTIONS